Camera listing based on comparison of imaging range coverage information to event-related data generated based on captured image

ABSTRACT

Event-related data based on an image that has been captured is generated. Coverage information relating to imaging range is compared to the event-related data. The cameras that can capture an image of the event, based on a comparing result, are listed so that an operator can select one of the listed cameras.

The present application is a Continuation application of Ser. No.18/140,306 filed on Apr. 27, 2023, which is a Continuation applicationof Ser. No. 17/123,737 filed on Dec. 16, 2020, which is a Continuationapplication of Ser. No. 16/295,150 filed on Mar. 7, 2019, which issuedas U.S. Pat. No. 10,893,240, which is a Continuation application of Ser.No. filed on Apr. 14, 2017, which issued as U.S. Pat. No. 10,362,274,which is a National Stage Entry of PCT/JP2015/005419 filed on Oct. 28,2015, which claims priority from Singapore Patent Application201407100-0 filed on Oct. 30, 2014, the contents of all of which areincorporated herein by reference, in their entirety.

TECHNICAL FIELD

The present invention relates to a monitoring system, a monitoringmethod and program for visual and/or audio. More specifically, thepresent invention relates to monitoring systems for detecting andreacting to abnormal events by real-time analysis technologies.

BACKGROUND ART

The real-time analysis technologies such as video analysis and audioanalysis can detect abnormal events in the field. Generally, operatorsmanually analyze data from sensors located near an event to become awareof a situation or to learn details of an event. The operators manuallyselect related information from periodic or continuous sensor data tobecome more aware of the situation or to learn more details of theevent. This procedure leads to delay in the operators' reaction toabnormal events because the analysis results and the sensor data usedfor the analysis may be insufficient to make a decision for respondingto the event.

SUMMARY OF INVENTION Technical Problem

What is needed is a system which can automatically select and controlsensors to show details of events including views providing a closerlook and overviews providing a wider look at the event as it unfolds sothat the operators can respond promptly based on the information in theviews provided. Furthermore, other desirable features andcharacteristics will become apparent from the subsequent detaileddescription and the appended claims, taken in conjunction with theaccompanying drawings and this background of the disclosure.

In view of above, a main object of the present invention is to provide amonitoring system and the like that can detect and react to abnormalevents in real-time.

Solution to Problem

An exemplary aspect of the present invention is a monitoring system forevent related data from a plurality of sensors, including: a receiverthat receives the event related data from a plurality of sensors; acoverage analyzer that analyzes predetermined data and the event relateddata from the receiver; and a sensor selector. The predetermined dataincludes sensor coverage information. The sensor selector is coupled tothe coverage analyzer and selects one or more of the plurality ofsensors based on the analysis by the coverage analyzer.

An exemplary aspect of the present invention is a monitoring method forevent related data from a plurality of sensors, including: receiving theevent related data from a plurality of sensors; analyzing predetermineddata and the event related data, the predetermined data including sensorcoverage information; and selecting one or more of the plurality ofsensors based on the analysis.

An exemplary aspect of the present invention is a non-transitorycomputer readable recording medium storing program for monitoring eventrelated data from a plurality of sensors, and the program causes acomputer to execute processing of: receiving the event related data froma plurality of sensors; analyzing predetermined data and the eventrelated data, the predetermined data including map information andsensor coverage information; and selecting one or more of the pluralityof sensors based on the analysis.

Advantageous Effects of Invention

According to the present invention, a monitoring system and the likethat can detect and react to abnormal events in real-time can beprovided.

BRIEF DESCRIPTION OF DRAWINGS

The accompanying figures, where like reference numerals refer toidentical or functionally similar elements throughout the separate viewsand which together with the detailed description below are incorporatedin and form part of the specification, serve to illustrate variousexemplary embodiments and to explain various principles and exemplaryadvantages in accordance with the present invention. Exemplary featuresand advantages of the present invention will become apparent from thefollowing detailed description when taken with the accompanying drawingsin which:

FIG. 1 is a schematic diagram of sensors used with a monitoring systemof a Related Art.

FIG. 2 is a schematic diagram of sensors used with a monitoring systemin accordance with the exemplary embodiments of the present invention.

FIG. 3 is a block diagram of a monitoring system in accordance with theexemplary embodiments of the present invention.

FIG. 4 is a flowchart in accordance with the exemplary embodiments ofthe present invention.

FIG. 5 is a block diagram of a monitoring system in accordance withanother embodiment of the present invention.

FIG. 6 is a flowchart in accordance with another embodiment of thepresent invention.

FIG. 7 is a schematic diagram of sensors used with a monitoring systemin a first exemplary embodiment of the present invention.

FIG. 8 is a schematic diagram of a first situation of the sensors usedwith the monitoring system in the first exemplary embodiment of thepresent invention.

FIG. 9 is a schematic diagram of a second situation of the sensors usedwith the monitoring system in the first exemplary embodiment of thepresent invention.

FIG. 10 is a schematic diagram of a third situation of the sensors usedwith the monitoring system in the first exemplary embodiment of thepresent invention.

FIG. 11 is a schematic diagram of a first situation of the sensors usedwith the monitoring system in a second exemplary embodiment of thepresent invention.

FIG. 12 is a schematic diagram of a second situation of the sensors usedwith the monitoring system in the second exemplary embodiment of thepresent invention.

FIG. 13A is a schematic diagram of a first situation of the sensors usedwith the monitoring system for multiple compartments in a thirdexemplary embodiment of the present invention.

FIG. 13B is a schematic diagram of another situation of the sensors usedwith the monitoring system for multiple compartments in the thirdexemplary embodiment of the present invention.

FIG. 14 is a block diagram of a monitoring system in a fourth exemplaryembodiment of the present invention.

FIG. 15 is a block diagram of an information processing apparatus torealize monitoring systems in exemplary embodiments of the presentinvention.

Skilled artisans will appreciate that elements in the figures areillustrated for simplicity and clarity and have not necessarily beendrawn to scale. For example, the dimensions of some of the elements inthe figures illustrating integrated circuit architecture may beexaggerated relative to other elements to help to improve understandingof the present and another exemplary embodiments.

DESCRIPTION OF EMBODIMENTS

The following detailed description is merely exemplary in nature and isnot intended to limit the invention or the application and uses of theinvention. Furthermore, there is no intention to be bound by any theorypresented in the preceding background of the invention or the followingdetailed description.

Firstly, a basic concept of exemplary embodiments of the presentinvention is described. Referring to FIG. 1 , sensors used with amonitoring system of a Related Art is shown. The system detects anabnormal event location 10 in an event area 12 by a first sensor(Microphone) 30 and selects a camera 32 which is the nearest camera tothe abnormal event location 10. However, the nearest camera 32 capturesonly a part of the abnormal event location 10 and the operators canreceive only limited information (information in a camera screen 34)regarding the abnormal event location 10 from the camera 32. In thiscase, since the nearest camera 32 captures a part of surrounding peopleinstead of people lying on the floor, the operators are not aware aperson or persons lying on the floor. The operators may try to learn thesituation by manually operating several sensors around the abnormalevent location 10. However, it takes time to learn what is happening andrespond to the event by e.g. calling a paramedic. In some cases, thedelay in response may become fatal.

Referring to FIG. 2 , sensors used with a monitoring system inaccordance with the exemplary embodiments of the present invention isshown. The monitoring system detects the abnormal event location 10 by afirst sensor 30 and estimates the abnormal event location 10 in theevent area 12. The monitoring system selects other sensors (camera 42and other sensors) which are located near the abnormal event location10. The other sensors' combined Field of View (FOV) for directionalfixed sensors and/or Field of Regarding (FOR) for non-directional ormovable sensors cover the entire event area 12. The monitoring systemcontrols the selected sensors (Microphone 30, Microphone 40 and/orcamera 42) to sense the detected abnormal event location 10. In thiscase, the selected sensor (camera 42) captures an entire event areaimage (by Camera 42) 46. Then, the operators become aware of theperson(s) lying on the floor without manual operation. Since theoperators are able to learn and respond to the situation without delay,it may be possible to deal with the situation before it gets fatal.

In accordance with the exemplary embodiments of the present invention,the operators can become aware of the event by learning details of theevent with a closer view of the event as well as the overview of theevent with a wider view because the monitoring system can select andcontrol sensors as described below. This advantageously enablesoperators to respond to events promptly.

Referring to FIG. 3 and FIG. 4 , a block diagram and a flow chart inaccordance with the exemplary embodiments of the present invention isdisclosed. The monitoring system 1000 continuously receives (step 200)sensor data from sensors (not shown) at sensor data receivers 100. Thesensor data receivers 100 send the received data to a coverage analyzer102. The coverage analyzer 102 executes a coverage analysis whichanalyzes the sensor coverage information by comparing the coverageinformation with the event related data such as size of the event and/ormovement of the event. The coverage analyzer 102 identifies the bestsensor(s) to observe an abnormal event at the abnormal event location 10(step 202). A sensor selector 104 selects one or more sensors (the bestsensor(s)) based on the coverage analysis (step 204) by the coverageanalyzer 102. Sensor actuators 106 actuate (step 206) one or moresensors in response to signals from the sensor selector 104. Thus, itcan be seen that the system of FIG. 3 operates in accordance with themethod of FIG. 4 to automatically select and actuate the best sensor(s)to observe the abnormal event as it unfolds. In this manner, theoperators can advantageously view the unfolding of the event and triggeran appropriate and timely response.

Referring to FIG. 5 and FIG. 6 , a block diagram and a flow chart inaccordance with another embodiment is disclosed. A monitoring system2000 in accordance with the another embodiment continuously receives(step 200) sensor data from sensors (not shown) at the sensor datareceivers 100 and analyzes the received data (step 208) by a dataanalyzer 108. When the sensor data receivers 100 send the received datato the data analyzer 108, the data analyzer 108 analyzes the receiveddata to identify event related information; that is, the abnormal eventlocation 10 and size of the event, and forwards this event relatedinformation to the coverage analyzer 102 (step 208). In this manner, thedata analyzer 108 continuously reviews the received data from the sensordata receivers 100 and, when the data analyzer 108 determines that anevent of interest to the operators is occurring, the data analyzer 108determines the abnormal event location 10 and the size of the event ofinterest and forwards the event related information to the coverageanalyzer 102 to trigger event coverage operation (coverage analysis) ofthe coverage analyzer 102. The coverage analyzer 102 then executes thecoverage analysis and identifies the best sensor(s) to observe the event(step 202) as it unfolds. The sensor selector 104 receives informationidentifying the best sensor(s) to observe the event and selects thesensor(s) for actuation in response to the information from the coverageanalysis (step 204). The sensor actuators 106 actuate the sensor(s)(step 206) so that the operators may advantageously follow the eventwith the best coverage available from the system.

The coverage analyzer 102 analyzes the coverage of each of the sensorsto identify suitable sensor(s) to observe the detected event. Thecoverage analyzer 102 analyzes the sensor coverage information bycomparing the coverage information with the event related data such assize of the event and/or movement of the event. Then, the coverageanalyzer 102 sends the result to the sensor selector 104 so that thesensor selector 104 can select a sensor nearest to the detected eventwhich has a Field Of View (FOV) for directional fixed sensors and aField of Regarding (FOR) for non-directional or movable sensors largeenough to capture the event.

The coverage analysis by the coverage analyzer 102 may include analysisbased on the type of event. There are several types of events to bemonitored and useful information for operators are different for eachtype of events. The coverage analyzer 102 in accordance with a presentembodiment is customized for the type of events and provides usefulinformation for operators for each event.

In one case scenario, the operators may be concerned about abandonedobjects in public areas because they may pose a security risk. Forexample, a system tracking objects at a train station may determinewhich ones remain stationary and then select a camera which can observethe object closely. In another case scenario, the operators may beconcerned about congestion. For monitoring congestion events, a part ofan event scene may be insufficient for operators to make a decision andrespond promptly. Therefore, a camera which can observe the event from apanoramic view is selected.

The coverage analysis by the coverage analyzer 102 may take into accountmap information. The map information includes information regarding wallor other space defining structures. In actual situations, coverages ofsensors tend to be blocked by various things. The coverage analyzer 102in accordance with a present embodiment takes into account things suchas walls or other space defining structures when determining optimalFOVs and/or FORs.

In one case scenario, there is a wall between the event location and acamera and the camera is not able to capture the event. To provideuseful information for operators, the camera which is not able tocapture the event due to the wall is excluded from a list of sensorselections and a camera which is able to capture the event is selected.If there is no camera which is able to capture the event area directly,then a microphone which is able to capture the area is selected.

Also, the coverage analysis by the coverage analyzer 102 may includeanalysis based on the capability of sensor actuators. The sensoractuators 106 are able to change sensor setting, such as pan-tilt-zoom(PTZ), based on the information from the sensor selector 104. Also, thesensor actuators 106 may be able to change a direction of sensors. Bytaking into account these capabilities of the sensor actuators 106 andthe sensors, the coverage of each sensor is identified and the bestsensor(s) to capture the event will be identified by the coverageanalysis 202 in accordance with the present embodiment.

First Exemplary Embodiment

Referring to FIG. 7 , a first exemplary embodiment of the presentinvention is disclosed. In this first embodiment, a monitoring system(monitoring system 2000) selects sensors which are suitable forobserving a detected event. Multisensory surveillance devices, such assurveillance cameras with microphones, are placed in a surveillancearea. An exemplary camera configuration in the surveillance area isshown as fixed cameras (32, 42, 52, 62 and 72) with microphones (30, 40,50, 60 and 70). A single sensor device such as a fixed camera withoutmicrophone or a microphone by itself may also be used. Sensor datareceivers 100 receive the data from these sensor devices and pass thedata to a data analyzer 108. The sensor data receivers 100 may processmedia conversion such as decoding, encoding, transcoding and resolutionconversion, if necessary.

The data analyzer 108 analyzes the data from the sensor devices. Thedata may include an abnormal crowd behavior such as a crowd gatheringand scattering detected by a camera. The data may also include anabnormal sound such as screaming or a breaking sound detected by amicrophone. The data analyzer 108 may analyze the data detected by asingle sensor or multiple sensors. The data analyzer 108 passes theresults of the data analysis to the coverage analyzer 102. The dataanalyzer 108 may pass metadata of the detected event such as location ofthe event, likelihood of the nature of the event, time of the event,possible event list and possible subsequent event candidates.

Referring to FIG. 8 , a first situation of the sensors used with themonitoring system 2000 of the first exemplary embodiment of the presentinvention is disclosed. The coverage analyzer 102 identifies sensorswhich are suitable to observe an event detected by the data analyzer108. The coverage analyzer 102 identifies sensor coverage informationfor each sensor such as a field of view (FOV) for directional fixedsensors or a field of regard (FOR) for non-directional or movablesensors. In one example, the coverage analyzer 102 identifies sensorsthat have FOV or FOR which overlaps with the detected event location.Regarding an event detected by a microphone 60, the coverage analyzer102 identifies the camera 32 instead of the camera 52 or the camera 62because a FOV 36 of the camera 32 has the largest overlapping FOV with aFOR 68 of the microphone 60. Also, regarding an event detected by thecamera 62, the coverage analyzer 102 identifies the camera 32 instead ofthe camera 52 because the FOV 36 of the camera 32 has a larger coveragearea overlapping with a FOV 66 of the camera 62 in comparison with a FOVof the camera 52.

Referring to FIG. 9 , a second situation of the first exemplaryembodiment of the present invention is disclosed. The coverage analyzer102 identifies a camera that has the FOV or FOR which covers a size ofthe event which is estimated by a data analyzer 108. Regarding an eventdetected by a microphone 60, the coverage analyzer 102 identifies thecamera 52 instead of the camera 32 or the camera 62. This is because theFOV 56 of the camera 52 covers the entire estimated event area of theabnormal event location 10 while the FOV of the camera 62 covers theevent partially. Also, the camera 52 is closer to the abnormal eventlocation 10 as compared with the camera 32. Therefore, the camera 52 isidentified by the coverage analyzer 102.

Referring to FIG. 10 , a third situation of the first exemplaryembodiment of the present invention is disclosed. The coverage analyzer102 identifies a camera based on map information including wall or otherspace defining structures. If there are walls or other space definingstructures within the coverage of the sensors, the coverage analysis 202takes into account the walls or other space defining structures.Regarding events detected by a microphone 40, the coverage analyzer 102identifies the microphone 40 and the microphone 30 instead of the camera52 because the view of the camera 52 is blocked by a wall 20. Since thewall or other space defining structures may have significant impact onidentification of sensors, taking into account map information incoverage analysis is helpful to provide accurate information to theoperators.

In another example, the coverage analyzer 102 may identify a camerabased on an installed configuration of the sensors. There are varioustypes of operator requirements. The operators may wish to obtaininformation concerning the surroundings of the event instead of theevent itself in some situations. In such situations, the coverageanalysis 202 based on the installed configuration of the sensors will beuseful for the operators. The coverage analyzer 102 may determine one ormore of the plurality of sensors that may capture an object or person asit/he/she moves away from an event location in response to the installedconfiguration of the sensors and the event related data. Also, thecoverage analyzer 102 may determine one or more of the plurality ofsensors that may monitor the unfolding event, the one or more of theplurality of sensors including at least one of the plurality of sensorsthat captures a large portion of space defined within the space definingstructures of the map information.

In accordance with the first exemplary embodiment in the presentinvention, the monitoring system can detect and react to abnormal eventsin real-time. The reason is that the coverage analyzer 102 analyzes thedata in accordance with a rule based algorithm method, a machinelearning algorithm method and/or a geographical map based algorithm.Also, the wall or other space defining structure information may beincluded in the FOV information instead of map information.

The coverage analyzer 102 may further analyze the data by combining oneor more algorithm methods in accordance with a Boolean formula, scoreresults of each of one or more of the algorithm methods in response to ascore of the results of each of the one or more of the algorithmmethods, and/or prioritize the results of the algorithm methods inresponse to predetermined priorities of each of the one or more of thealgorithm methods. The coverage analyzer 102 may analyze the data inaccordance with the machine learning algorithm method where the machinelearning algorithm method is based on an AdaBoost which considers thesealgorithm methods as weak learners. Further, the coverage analyzer 102may analyze the data in accordance with a clustering algorithm in orderto cluster the plurality of sensors into one or more suitable sensorclusters and one or more unsuitable sensor clusters.

The coverage analyzer 102 passes the identified sensor information tothe sensor selector 104. The sensor selector 104 selects sensors andsends the selected sensor information to the sensor actuators 106. Thesensor selector 104 may pass metadata such as event information to thesensor actuators 106. The sensor selector 104 may also pass a sensorlist and the metadata to an application system for presentation to theoperators to encourage them to monitor the selected sensors. The sensorselector 104 may also select more than one sensor. When the sensorselector 104 selects multiple sensors, the sensor selector 104 mayoutput the list of sensors with sensor prioritization scores indicatinga prioritization or ranking of optimal sensors.

The sensor actuators 106 may change sensor settings based on theinformation from the sensor selector 104 if necessary. To capture aregional event and observe the event closely, the sensor actuators 106may change sensor settings by changing volume, resolution or PTZ zoomsettings for optimal close up coverage of the event location. Also, tocapture a wide area event and to observe the entire scene of the event,the sensor actuators 106 change sensor settings by changing volume,resolution or PTZ zoom settings for optimal wide area coverage of theevent location.

Second Exemplary Embodiment

In a second exemplary embodiment of the present invention, themonitoring system does not select suitable sensors but instead listcandidates for various viewings. The viewings include but are notlimited to various views surrounding the event. The monitoring systemcaptures the event area from zoom out cameras to learn what is happeningaround the event. Alternatively, the monitoring system captures the exitof a room when an event occurs in the room. The viewings may alsoinclude viewing the subject of the event up close. The monitoring systemcaptures the event closely to learn the subject or cause of the event.

The coverage analyzer 102 determines one or more of the plurality ofsensors that may monitor the unfolding event and outputs selection datato the sensor selector 104 including identification of the one or moreof the plurality of sensors that may monitor the unfolding event.

Referring to FIG. 11 , the coverage analyzer 102 identifies sensors forthe various viewings. For example, the viewings include identifying acamera based on the FOV or FOR coverage of the event. In this example,the coverage analyzer 102 identifies the camera 32 to view thesurroundings of the abnormal event location 10 as detected by themicrophone 60 because the FOV of the camera 32 covers the surroundingsof the abnormal event location 10. Also, the coverage analyzer 102identifies the camera 52 to view the subject of the event detected bythe microphone 60 closely because the FOV of the camera 52 covers theabnormal event location 10 and the camera 52 is closer to the abnormalevent location 10 as compared with the camera 32. Therefore, the systemlists cameras 32 and 52 with their viewings (e.g., close up, wide area)so that the operators may select each view based on desired viewings.

Referring to FIG. 12 , the viewings also include identifying the camerabased on the FOV and/or the FOR coverage. In this example, the coverageanalyzer 102 identifies the camera 32 to view the surroundings of theevent detected by the microphone 60 because the FOV of the camera 32 hasthe largest FOV overlapping with the FOR of the microphone 60. Also, thecoverage analyzer 102 identifies the camera 52 to view the subject ofthe event detected by the microphone 60 up close because the FOV of thecamera 52 has overlapping coverage with the FOR of the microphone 60 andthe camera 52 is close to the microphone 60. Therefore, in this examplethe system lists camera 32 and 52 so that operators may select each viewbased on desired viewings.

The coverage analyzer 102 passes the result to the sensor selector 104.The sensor selector 104 passes information to the sensor actuators 106which includes viewing information. The sensor selector 104 may pass thesensor list and metadata to an application system which presentsinformation to users/operators to encourage the users to monitor one ormore of the selected sensors. The sensor actuators 106 may change sensorsettings based on the viewing information from the sensor selector 104if necessary. The sensor selector 104 selects one or more of theplurality of sensors in response to the selection data for operatormonitoring. The selection data includes sensor prioritization scores.The sensor selector selects more than one of the plurality of sensors inresponse to the selection data for operator monitoring in accordancewith the sensor prioritization scores. The sensor selector furtheroutputs a list of one or more of the plurality of sensors along withcorresponding sensor prioritization scores for suggested optimaloperator monitoring.

In accordance with the second exemplary embodiment in the presentinvention, the monitoring system can detect and react to abnormal eventsin real-time. The reason is that operators may select each of viewsbased on list candidates for various viewings. The viewings include butare not limited to various views surrounding the event. The systemcaptures the event area from zoom out cameras to learn what is happeningaround the event.

Third Exemplary Embodiment

In a third exemplary embodiment of the present invention, the coverageanalyzer 102 may use the map information for sensor coverage analysisand sensor identification. In this third exemplary embodiment, there aremultiple compartments in the surveillance field and each compartment hasone or more cameras and/or microphones. The sound can be detected by notonly the microphone in one of the compartments but also by microphonesin nearby compartments. Therefore, the system is required to identifythe event location and be capable of selecting the camera in thecompartment where the event occurs.

Referring to FIG. 13A and FIG. 13B, one of the plurality of sensors is amicrophone. A sensor data receiver 100 receives the event related datafrom the microphone including a direction of an audio input. Thecoverage analyzer 102 uses this direction information from multiplemicrophones. If the sound came from inside a compartment, then thesystem selects the camera in the compartment. In the FIG. 13A case, thesystem selects the camera 42 because the microphone 40 detected that thesound was coming from inside the compartment containing the camera 42.Furthermore, the other microphones 30, 50 and 60 detected the sounddirection which can be interpreted by the coverage analyzer 102 as thesound comes from the compartment monitored by the camera 42.

On the other hand, if all sounds were from outside of the compartments,then the system selects the camera which captures the outside of thecompartments. In the FIG. 13B case, the system selects the camera 72because all the microphones 30, 40, 50 and 60 detected that the soundcame from outside all of the compartments.

In accordance with the third exemplary embodiment in the presentinvention, the monitoring system can detect and react to abnormal eventsin real-time. The reason is that the coverage analyzer 102 may use themap information for sensor coverage analysis and sensor identification.

Fourth Exemplary Embodiment

A monitoring system 1 in a fourth exemplary embodiment of the presentinvention is described by referring to FIG. 14 . The monitoring system 1of the fourth exemplary embodiment includes a receiver 2, a coverageanalyzer 3 and a sensor selector 4.

The receiver 2 receives the event related data from a plurality ofsensors. The coverage analyzer 3 analyses predetermined data and theevent related data from the receiver, the predetermined data includingmap information and sensor coverage information. The sensor selector 4is coupled to the coverage analyzer 3 and selects one or more of theplurality of sensors based on the analysis by the coverage analyzer 3.

In accordance with the fourth exemplary embodiment in the presentinvention, the monitoring system 1 can detect and react to abnormalevents in real-time. The reason is that the coverage analyzer 3 analyzespredetermined data and the event related data from selectable receiversto show details of events including desired views.

It should further be appreciated that the exemplary embodiments are onlyexamples, and are not intended to limit the scope, applicability,dimensions, or configuration of the invention in any way. Rather, theforegoing detailed description will provide those skilled in the artwith a convenient road map for implementing an exemplary embodiment ofthe invention, it being understood that various changes may be made inthe function and arrangement of elements and method of fabricationdescribed in an exemplary embodiment without departing from the scope ofthe invention as set forth in the appended claims.

FIG. 15 illustrates, by way of example, a configuration of aninformation processing apparatus 900 (computer) which can implement amonitoring system relevant to an exemplary embodiment of the presentinvention. In other words, FIG. 15 illustrates a configuration of acomputer (information processing apparatus) capable of implementing thesystem in FIGS. 2, 7-13B, representing a hardware environment where theindividual functions in the above-described exemplary embodiments can beimplemented.

The information processing apparatus 900 illustrated in FIG. 15 includesthe following as components:

-   -   CPU 901 (Central_Processing_Unit);    -   ROM 902 (Read_Only_Memory);    -   RAM 903 (Random_Access_Memory);    -   Hard disk 904 (storage device);    -   Communication interface to an external device 905 (Interface:        hereinafter called “I/F”);    -   Reader/writer 908 capable of reading and writing data stored in        a storage medium 907 such as CD-ROM        (Compact_Disc_Read_Only_Memory); and    -   Input/output interface 909.

The information processing apparatus 900 is a general computer wherethese components are connected via a bus 906 (communication line).

The present invention explained with the above-described exemplaryembodiments as examples is accomplished by providing the informationprocessing apparatus 900 illustrated in FIG. 15 with a computer programwhich is capable of implementing the functions illustrated in the blockdiagrams (FIGS. 3, 5, 14 ) or the flowcharts (FIGS. 3, 5 ) referenced inthe explanation of these embodiments, and then by reading the computerprogram into the CPU 901 in such hardware, interpreting it, andexecuting it. The computer program provided to the apparatus can bestored in a volatile readable and writable storage memory (RAM 903) orin a non-volatile storage device such as the hard disk 904.

In addition, in the case described above, general procedures can now beused to provide the computer program to such hardware. These proceduresinclude, for example, installing the computer program into the apparatusvia any of various storage media 907 such as CD-ROM, or downloading itfrom an external source via communication lines such as the Internet. Inthese cases, the present invention can be seen as being composed ofcodes forming such computer program or being composed of the storagemedium 907 storing the codes.

This application is based upon and claims the benefit of priority fromSingapore Patent Application No. 201407100-0, filed on Oct. 30, 2014,the disclosure of which is incorporated herein in its entirety byreference.

The previous description of the embodiments is provided to enable aperson skilled in the art to make and use the present invention.Moreover, various modifications to these exemplary embodiments will bereadily apparent to those skilled in the art, and the generic principlesand specific examples defined herein may be applied to other embodimentswithout the use of inventive faculty. Therefore, the present inventionis not intended to be limited to the exemplary embodiments describedherein but is to be accorded the widest scope as defined by thelimitations of the claims and equivalents. Further, it is noted that theinventor's intent is to retain all equivalents of the claimed inventioneven if the claims are amended during prosecution.

REFERENCE SIGNS LIST

-   -   10 Abnormal event location    -   12 Event area    -   14 Direction of sound    -   20 Wall    -   30 Microphone    -   32 Camera    -   34 Image by Camera 32    -   36 Field of View of Camera 32    -   40 Microphone    -   42 Camera    -   44 Field of View of Camera 42    -   46 Image by Camera 42    -   50 Microphone    -   52 Camera    -   56 Field of View of Camera 52    -   60 Microphone    -   62 Camera    -   66 Field of View of Camera 62    -   68 Field of Regarding of Microphone 60    -   70 Microphone    -   72 Camera    -   100 Sensor data receiver    -   102 Coverage analyzer    -   104 Sensor selector    -   106 Sensor actuator    -   108 Data analyzer    -   200 Sensor data receive    -   202 Coverage analysis    -   204 Sensor selection    -   206 Sensor actuation    -   208 Data analysis

1. A surveillance control system controlling a plurality of sensorscomprising: at least one memory storing instructions; and at least oneprocessor connected to the memory that, based on the instructions,performs operations comprising: receiving sensor data including eventrelated data relating to at least one of scale of the event andoccurrence location of the event from at least one of the plurality ofsensors; selecting at least one of the plurality of sensors based oncapability of sensor actuators of the plurality of sensors, the sensordata and coverage information relating to imaging range which each ofthe plurality of sensors is able to image; and actuating the selected atleast one of the plurality of sensors.
 2. The surveillance controlsystem according to claim 1, the operations further comprising:comparing the coverage information with the sensor data; and selectingat least one of the plurality of cameras based on the comparing result.3. The surveillance control system according to claim 1, the operationsfurther comprising: selecting at least one of the plurality of sensorsbased on the type of the event.
 4. The surveillance control systemaccording to claim 1, the operations further comprising: in theselecting, identifying at least one of the plurality of sensors based onmap information including wall or other space defining structures. 5.The surveillance control system according to claim 1, the operationsfurther comprising: selecting at least one of the plurality of sensorsby changing at least one of direction, resolution or pan-tilt-zoom (PTZ)settings of at least one of the plurality of sensors.
 6. Thesurveillance control system according to claim 1, wherein the coverageinformation includes information concerning Field of View (FOV) of theplurality of sensors.
 7. The surveillance control system according toclaim 1, wherein the coverage information includes information Field ofRegard (FOR) for non-directional or movable sensors included in theplurality of sensors.
 8. The surveillance control system according toclaim 1, wherein the selecting includes selecting the at least one ofthe plurality of sensors further based on map information concerningwall or other space defining structures.
 9. A surveillance controlmethod controlling a plurality of sensors comprising: receiving sensordata including event related data relating to at least one of scale ofthe event and occurrence location of the event from at least one of theplurality of sensors; selecting at least one of the plurality of sensorsbased on capability of sensor actuators of the plurality of sensors, thesensor data and coverage information relating to imaging range whicheach of the plurality of sensors is able to image; and actuating theselected at least one of the plurality of sensors.
 10. The surveillancecontrol method according to claim 9, further comprising: comparing thecoverage information with the sensor data; and selecting at least one ofthe plurality of cameras based on the comparing result.
 11. Thesurveillance control method according to claim 9, further comprising:selecting at least one of the plurality of sensors based on the type ofthe event.
 12. The surveillance control method according to claim 9,further comprising: in the selecting, identifying at least one of theplurality of sensors based on map information including wall or otherspace defining structures.
 13. The surveillance control method accordingto claim 9, further comprising: selecting at least one of the pluralityof sensors by changing at least one of direction, resolution orpan-tilt-zoom (PTZ) settings of at least one of the plurality ofsensors.
 14. The surveillance control method according to claim 9,wherein the coverage information includes information concerning Fieldof View (FOV) of the plurality of sensors.
 15. The surveillance controlmethod according to claim 9, wherein the coverage information includesinformation Field of Regard (FOR) for non-directional or movable sensorsincluded in the plurality of sensors.
 16. The surveillance controlmethod according to claim 9, wherein the selecting includes selectingthe at least one of the plurality of sensors further based on mapinformation concerning wall or other space defining structures.
 17. Anon-transitory computer readable storage medium causing a computercontrolling a plurality of sensors to execute operations comprising:receiving sensor data including event related data relating to at leastone of scale of the event and occurrence location of the event from atleast one of the plurality of sensors; selecting at least one of theplurality of sensors based on capability of sensor actuators of theplurality of sensors, the sensor data and coverage information relatingto imaging range which each of the plurality of sensors is able toimage; and actuating the selected at least one of the plurality ofsensors.
 18. The non-transitory computer readable storage mediumaccording to claim 17, the operations further comprising: comparing thecoverage information with the sensor data; and selecting at least one ofthe plurality of cameras based on the comparing result.
 19. Thenon-transitory computer readable storage medium according to claim 17,the operations further comprising: selecting at least one of theplurality of sensors based on the type of the event.
 20. Thenon-transitory computer readable storage medium according to claim 17,the operations further comprising: in the selecting, identifying atleast one of the plurality of sensors based on map information includingwall or other space defining structures.